Python framework for optimizing multi-energy systems.
Project description
odys
- Github repository: https://github.com/ramirocrc/odys/
- Documentation https://ramirocrc.github.io/odys/
Odys is a Python package for optimizing multi-asset energy portfolios across multiple electricity markets using stochastic optimization, powered by Pydantic, linopy, and HiGHS .
The key features are:
- Intuitive to write: Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs.
- Simple API: Define your energy system (generators, batteries, loads, markets) and call .optimize(). The mathematical model is built and solved for you under the hood.
- Pydantic-powered validation: All models are built on Pydantic with strict typing and validators, catching configuration errors early.
- Stochastic optimization: Optimize across multiple probabilistic scenarios with different prices, capacities, and load profiles to make decisions under uncertainty.
Requirements
A recent and currently supported version of Python.
As Odys is based on Pydantic, linopy, and HiGHS, they will be automatically installed when you install odys.
Installation
pip:
pip install odys
uv:
uv add odys
Example
A generator and a battery working together to meet a fixed load over 4 hourly timesteps:
from datetime import timedelta
from odys.energy_system import EnergySystem
from odys.energy_system_models.assets.generator import PowerGenerator
from odys.energy_system_models.assets.load import Load
from odys.energy_system_models.assets.portfolio import AssetPortfolio
from odys.energy_system_models.assets.storage import Battery
from odys.energy_system_models.scenarios import Scenario
generator = PowerGenerator(
name="gen",
nominal_power=100.0,
variable_cost=50.0,
)
battery = Battery(
name="battery",
capacity=50.0,
max_power=25.0,
efficiency_charging=0.95,
efficiency_discharging=0.95,
soc_start=0.5,
soc_end=0.5,
)
load = Load(name="demand")
portfolio = AssetPortfolio()
portfolio.add_asset(generator)
portfolio.add_asset(battery)
portfolio.add_asset(load)
energy_system = EnergySystem(
portfolio=portfolio,
scenarios=Scenario(
load_profiles={"demand": [60, 90, 40, 70]},
),
timestep=timedelta(hours=1),
number_of_steps=4,
power_unit="MW",
)
result = energy_system.optimize()
Contributing
For guidance on setting up a development environment and how to make a contribution to odys, see Contributing to odys.
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